The idea behind FlowMo came from my 2021 ME Mechanical Engineering thesis project. The title of my thesis was "Performance Enhancements of Fluidic Devices via Geometrical Optimisation".
The code in this repository is the genetic algorithm that I developed as part of my thesis project.
The genetic algorithm exploits computational fluid dynamics (CFD) simulations to geometrically optimise the design of a fluidic device. More specifically, the genetic algorithm is used to create and optimise a method of controlling flow in FoodMarble AIRE, a hydrogen breath testing device which aids in identifying trigger foods for users with irritable bowel syndrome and food intolerances. FoodMable is a start-up set by UCD alumni, where I did an 8-month placement during my studies at UCD. The title of the thesis was one I put forward to the engineering school and is based on a real-life problem I came across while working in FoodMarble. I felt that the problem could be solved through the application of engineering principles. The genetic algorithm created a design that showed good potential as a flow control device for FoodMarble’s application. Moreover, towards the end of my thesis project it became apparent to me that the algorithmic approach presented a unique approach of creating fluidic devices that can be applied to a range of flow control applications.